BioPerspectives

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Dec 13, 2010

Racing Down the Critical Path

The clock is ticking. With each passing second your biotech company is burning capital, value that will not be fully repaid even with extensions on exclusivity when your product is FDA-approved. Or perhaps you're a patient, anxiously awaiting any new hope for your terrible malady.

Patients and manufacturers alike pay the price for long regulatory periods, but remedies must be proven. Several consultancies exist solely to guide companies along the FDA's critical path from drug discovery to approval.

The FDA's CDRH (devices) director, Jeffrey Shuren, M.D., addressed other issues noted in the report, such as greater cost and time to market with the FDA; on the subject of satisfaction he only noted that 20% was not a sufficient response rate for the survey—40% might be better.

We can tell from the data that at least 12% of all U.S. medical device manufacturers have a better opinion of the European Commission than the FDA. There are patients who think the next wonder drug or device is locked up in regulatory limbo and others who are horrified to see drugs they have been living on for years now removed from the market, while personal injury lawyers flock to capitalize on new potential lawsuits. On the other hand, there are those who are harmed by unsafe products or killed by unforeseen interactions. The responsibilities of the FDA are certainly unenviable.

While the FDA may seem lumbering and gargantuan, it is not immutable: The past century saw dozens of legislative amendments and internal reforms adapting the FDA's resources to approach new responsibilities, technologies, and climates. With all these modifications, adding regulatory tools, approval pathways, departments, and responsibilities to the FDA, one might think that the FDA would have finer-grained control over its responses to products—and to some extent, it does.

HIV/AIDS provoked changes to allow patients to access experimental drugs, and the FDA has been making use of its ability to approve drugs for specific patient populations. But, when it comes down to it, the FDA currently only has a binary option: To approve or not (possibly with a request for more studies).

Regulatory Science Initiative

The state of the art is ever-changing, and the latest dispatches from the FDA acknowledge it. "Advancing Regulatory Science for Public Health" details a number of changes that the FDA will make with its new $25 million budget.

With respect to emerging technologies, the FDA promises to build expertise and regulatory frameworks for new nanotech and biotech products. It is much needed; we stand at the cusp of a new era of intelligent medications, from nanomachines with basic targeting and controlled-release mechanisms to tumor-killing bacteria and other whole-cell therapies.

Imagine how the FDA would approach tumor-killing bacteria, a living system with genetically encoded logic, intended for systemic use? Other living organisms such as maggots and leeches have been approved under Class II regulations (medical devices with special controls).

Stem cell therapies may also be comparable, and they fall under either human tissue or biologic regulations. But would engineered bacteria be a biologic or a device? What about symbiotic gut bacteria engineered to treat lactose intolerance, which would be long-term residents? What if they were the drug-delivery mechanism?

Under the section discussing "Accelerating the Delivery of New Medical Treatments to Patients"—a topic anxiously followed by patients, manufacturers, and investors alike—the FDA's involvement in a truly unusual drug trial is perhaps most interesting. Titled "I-SPY 2," the trial (started in March 2010) is supported by a pharma/NIH/FDA partnership. Breaking with tradition, IND approval was given for the trial itself. Test compounds can be added or removed without reapproving the protocol, and biomarkers will be used to better identify patient populations and match them with the appropriate drugs. Might this become the norm?

Under the heading of "bioinformatics," FDA proposes to enhance its monitoring of products by "mining complex data from clinical trials, healthcare settings, and biological studies." They certainly have their work cut out for them.

Take the healthcare setting: Even with electronic health record (EHR) uptake spurred by stimulus funds, only 10% of physicians responding to a 2010 CDC survey had "fully functional" electronic health records, a category that still does not require the ability to electronically report notifiable diseases or adverse events using these systems. In that survey, there are fifteen different brands of EHRs listed, with space for "other" systems. With so much variation, it is important to develop secure data standards and soon.

Imagine a New FDA

Say a drug, a device, or some other health product has come out of a lab with its efficacy and cytotoxicity demonstrated in vitro and perhaps in vivo in animals or in silico; the mechanism of action has been elucidated and a patent was filed. At this point we would be looking at IND approval for the drug and then seven plus years until approval, during which millions would be spent on clinical trials.

Is the Phase I/II/III/IV model really the best for a wide variety of potential phenotypes? How many departments do we need?

I envision an FDA with a unified, gradual pathway to market (removing confusion about which procedure to use for unusual submissions) and an extensive, linked knowledge base. Starting at the IND approval point (or its equivalent), a new product would be tested in its smallest target patient population—a few patients, extensively characterized with genotyping and other biomarkers—that most closely matches the nonpatient test conditions.

If the drug was tested on cells with mutations x, y, and z, the patients would ideally have similar genotypes, at least in relevant loci. “Relevant” for drugs might mean cytochrome P450 genes, which play a prime role in drug metabolism and biological half-life. A mutation in one of these could spell the difference between life and death for a given dosage. Careful measurement of biological indicators can give early warning of adverse effects, and, as dosage is ramped up from nontherapeutic “safe” levels to therapeutic levels, efficacy can be measured using these indicators.

More patients can be added as safety and efficacy accumulate more evidence in support. And at some point, when the patient population is no longer expanding exponentially, the product will switch over from experimental to marketable. The patients get their drugs sooner, and Phase I/II/III data is wrapped into one and returns sooner, allowing faster approval.

If adverse reactions are detected in the post-approval monitoring, these reactions can be analyzed to identify risk factors, the mechanism examined, and measures taken to prevent at-risk cases from receiving the treatment, all without interrupting the treatment of those not at risk. If further investigation is needed, researchers would be able to request additional information about the participants through questionnaires. The collected data can then be applied to similar compounds, allowing improved formulations to hit the market sooner.

This would truly be personalized drug (and device) development, and it relies on several technologies: secure sharing of personal health records, cost-effective DNA sequencing, better instrumentation and biological indicators, and connected research and clinical trial databases along with software to analyze the whole mess of data. I would argue that these technical developments will not be the limiting factor.

The challenge lies in how organizational frameworks will have to be laid out. Patient rights in this new context will also have to be evaluated. Additionally, exclusivity will have to be adjusted to ensure incentives are preserved.

Now is the perfect time to start figuring this out, with a pilot case of flexible trials (I-SPY 2) and several technological improvements in progress. Will the FDA fix the critical path in time for the next race?

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